The development of systems for assisting security attempts to address the need to secure numerous critical infrastructures with the aid of spot control spaces. To optimize these systems, current studies favor multiplication of the detectors making it possible to cover a wide spectrum of dangerous substances or elements. However, the sensitivity and specificity of detectors make it necessary to aggregate their alarms so as to yield robust and reliable analysis elements. Within this framework, numerous systems for assisting security integrate a module for 3D video tracking of people allowing them to merge possible alarms corresponding to one and the same person. The tracking module makes it possible to track each person present in the secure zone, and therefore makes it possible to associate each alarm arising from a sensor with a tracked person. Thus it is possible to aggregate several detections with one and the same person over time and to strengthen the assumption of danger up to a probability which is sufficient to forewarn a security operator.
However, modules for tracking people offer limited reliability and may fairly easily confuse two people when they interact, crossing one another, walking in proximity, sometimes facing one another.
To alleviate this problem, two known approaches exist to date.
The first approach consists in arranging matters such that the people present in the zone secured by the control system remain well separated so as to avoid situations of interactions or potential errors for the tracking modules. Thus, patent EP 2 204 783 A1 from Thales proposes a security system where a single person must pass through a security corridor. This solution is viable in a very constrained context, this being less and less accepted by operatives.
The second approach consists in carrying out long-term probabilistic analyses based on various criteria regarding appearances and/or morphologies, so as to attempt to recognize the various people that have interacted once they have been separated. Several known algorithms make it possible to manage multiple assumptions, so as not to take an immediate decision to associate the detections of people with a track, a track being associated with a series of positions of people in space and time, and then to wait to have sufficient elements to confirm or deny the pairings between tracks and detections. Thus, the article by B. Song and A. K. Roy-Chowdhury entitled “Stochastic Adaptive Tracking In A Camera Network”, or the article by R. Y. Khalaf and S. S. Intille entitled “Improving multiple people tracking using temporal consistency” propose variants around this principle. The drawback of this so-called “probabilistic analyst” approach is that it integrates uncertainty and doubt. It does not therefore integrate the specific constraints of security systems in terms of reliability.
However, the reliability of a security system presupposes that the latter must have a rate of non-detection of danger that is almost zero.
Thus, existing solutions do not address the recent problematic issue posed by new security assistance systems. To address recent requirements for securing critical infrastructures, these systems may not impose the constraint of perfect separability of people in secure zones, both in respect of hardware constraints (with the need for numerous operators to control circulation or for physical barriers) and in respect of constraints of operability of these systems.
Thus the need exists for a solution which alleviates the drawbacks of the known solutions.
The present invention addresses this need.